



'''simple docstring'''






import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
     from transformers.pipelines.conversational import Conversation

lowerCAmelCase:   Any					=		logging.get_logger(__name__)


lowerCAmelCase:   List[str]					=		{
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

lowerCAmelCase:   Union[str, Any]					=		{
    'vocab_file': {'facebook/blenderbot-3B': 'https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json'},
    'merges_file': {'facebook/blenderbot-3B': 'https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt'},
    'tokenizer_config_file': {
        'facebook/blenderbot-3B': 'https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json'
    },
}

lowerCAmelCase:   List[Any]					=		{'facebook/blenderbot-3B': 1_2_8}
@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def  lowerCamelCase__			(		):
  a		:   Any	  =	(
      list(range(ord('!'							)					,     ord('~'							) + 1							)							) + list(range(ord('¡'							)					,     ord('¬'							) + 1							)							) + list(range(ord('®'							)					,     ord('ÿ'							) + 1							)							)
  )
  a		:   Dict	  =	bs[:]
  a		:   Any	  =	0
  for b in range(2**8							):
    if b not in bs:
      bs.append(_A							)
      cs.append(2**8 + n							)
      n += 1
  a		:   Any	  =	[chr(_A							) for n in cs]
  return dict(zip(_A					,     _A							)							)
def  lowerCamelCase__			(		_A							):
  a		:   Tuple	  =	set()
  a		:   str	  =	word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)							)
    a		:   int	  =	char
  return pairs

class 				a__(   lowerCamelCase__      ):
    lowercase__					=       VOCAB_FILES_NAMES
    lowercase__					=       PRETRAINED_VOCAB_FILES_MAP
    lowercase__					=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowercase__					=       ["""input_ids""", """attention_mask"""]







    def __init__( self					:    str		,     __snake_case					:    List[Any]		,     __snake_case					:    Optional[Any]		,     __snake_case					:    Union[str, Any]="replace"		,     __snake_case					:    List[Any]="<s>"		,     __snake_case					:    List[str]="</s>"		,     __snake_case					:    Dict="</s>"		,     __snake_case					:    Tuple="<s>"		,     __snake_case					:    List[Any]="<unk>"		,     __snake_case					:    List[str]="<pad>"		,     __snake_case					:    Any="<mask>"		,     __snake_case					:    Any=False		,     **__snake_case					:    Any		,     ):
      a		:   Dict	  =	AddedToken(__snake_case		,     lstrip=__snake_case		,     rstrip=__snake_case      ) if isinstance(__snake_case		,     __snake_case      ) else bos_token
      a		:   Dict	  =	AddedToken(__snake_case		,     lstrip=__snake_case		,     rstrip=__snake_case      ) if isinstance(__snake_case		,     __snake_case      ) else eos_token
      a		:   Any	  =	AddedToken(__snake_case		,     lstrip=__snake_case		,     rstrip=__snake_case      ) if isinstance(__snake_case		,     __snake_case      ) else sep_token
      a		:   Tuple	  =	AddedToken(__snake_case		,     lstrip=__snake_case		,     rstrip=__snake_case      ) if isinstance(__snake_case		,     __snake_case      ) else cls_token
      a		:   List[str]	  =	AddedToken(__snake_case		,     lstrip=__snake_case		,     rstrip=__snake_case      ) if isinstance(__snake_case		,     __snake_case      ) else unk_token
      a		:   Tuple	  =	AddedToken(__snake_case		,     lstrip=__snake_case		,     rstrip=__snake_case      ) if isinstance(__snake_case		,     __snake_case      ) else pad_token

      # Mask token behave like a normal word, i.e. include the space before it
      a		:   Union[str, Any]	  =	AddedToken(__snake_case		,     lstrip=__snake_case		,     rstrip=__snake_case      ) if isinstance(__snake_case		,     __snake_case      ) else mask_token

      super().__init__(
          errors=__snake_case		,     bos_token=__snake_case		,     eos_token=__snake_case		,     unk_token=__snake_case		,     sep_token=__snake_case		,     cls_token=__snake_case		,     pad_token=__snake_case		,     mask_token=__snake_case		,     add_prefix_space=__snake_case		,     **__snake_case		,     )

      with open(__snake_case		,     encoding='utf-8'      ) as vocab_handle:
        a		:   Any	  =	json.load(__snake_case      )
      a		:   Tuple	  =	{v: k for k, v in self.encoder.items()}
      a		:   str	  =	errors  # how to handle errors in decoding
      a		:   Any	  =	bytes_to_unicode()
      a		:   str	  =	{v: k for k, v in self.byte_encoder.items()}
      with open(__snake_case		,     encoding='utf-8'      ) as merges_handle:
        a		:   Any	  =	merges_handle.read().split('\n'      )[1:-1]
      a		:   Any	  =	[tuple(merge.split()      ) for merge in bpe_merges]
      a		:   List[Any]	  =	dict(zip(__snake_case		,     range(len(__snake_case      )      )      )      )
      a		:   str	  =	{}
      a		:   str	  =	add_prefix_space

      # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
      a		:   List[Any]	  =	re.compile(r'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'      )







    @property
    # Copied from transformers.models.roberta.tokenization_roberta.RobertaTokenizer.vocab_size with Roberta->Blenderbot, RoBERTa->Blenderbot
    def      lowercase_			( self					:    Union[str, Any]      ):
      return len(self.encoder      )







    def      lowercase_			( self					:    List[Any]      ):
      return dict(self.encoder		,     **self.added_tokens_encoder      )







    def      lowercase_			( self					:    str		,     __snake_case					:    Optional[int]      ):
      if token in self.cache:
        return self.cache[token]
      a		:   str	  =	tuple(__snake_case      )
      a		:   Union[str, Any]	  =	get_pairs(__snake_case      )

      if not pairs:
        return token

      while True:
        a		:   int	  =	min(__snake_case		,     key=lambda __snake_case      : self.bpe_ranks.get(__snake_case		,     float('inf'      )      )      )
        if bigram not in self.bpe_ranks:
          break
        a  ,      a		:   Optional[Any]	  =	bigram
        a		:   Optional[Any]	  =	[]
        a		:   Tuple	  =	0
        while i < len(__snake_case      ):
          try:
            a		:   List[Any]	  =	word.index(__snake_case		,     __snake_case      )
          except ValueError:
            new_word.extend(word[i:]      )
            break
          else:
            new_word.extend(word[i:j]      )
            a		:   Optional[int]	  =	j

          if word[i] == first and i < len(__snake_case      ) - 1 and word[i + 1] == second:
            new_word.append(first + second      )
            i += 2
          else:
            new_word.append(word[i]      )
            i += 1
        a		:   Optional[int]	  =	tuple(__snake_case      )
        a		:   int	  =	new_word
        if len(__snake_case      ) == 1:
          break
        else:
          a		:   List[str]	  =	get_pairs(__snake_case      )
      a		:   Optional[Any]	  =	' '.join(__snake_case      )
      a		:   List[str]	  =	word
      return word







    def      lowercase_			( self					:    Dict		,     __snake_case					:    Dict      ):
      a		:   Optional[Any]	  =	[]
      for token in re.findall(self.pat		,     __snake_case      ):
        a		:   Tuple	  =	''.join(
            self.byte_encoder[b] for b in token.encode('utf-8'      )      )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
        bpe_tokens.extend(bpe_token for bpe_token in self.bpe(__snake_case      ).split(' '      )      )
      return bpe_tokens







    def      lowercase_			( self					:    Any		,     __snake_case					:    Tuple      ):
      return self.encoder.get(__snake_case		,     self.encoder.get(self.unk_token      )      )







    def      lowercase_			( self					:    Dict		,     __snake_case					:    Tuple      ):
      return self.decoder.get(__snake_case      )







    def      lowercase_			( self					:    Dict		,     __snake_case					:    Union[str, Any]      ):
      a		:   Optional[Any]	  =	''.join(__snake_case      )
      a		:   int	  =	bytearray([self.byte_decoder[c] for c in text]      ).decode('utf-8'		,     errors=self.errors      )
      return text







    def      lowercase_			( self					:    str		,     __snake_case					:    str		,     __snake_case					:    Optional[str] = None      ):
      if not os.path.isdir(__snake_case      ):
        logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""      )
        return
      a		:   List[str]	  =	os.path.join(
          __snake_case		,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']      )
      a		:   Optional[int]	  =	os.path.join(
          __snake_case		,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']      )

      with open(__snake_case		,     'w'		,     encoding='utf-8'      ) as f:
        f.write(json.dumps(self.encoder		,     indent=2		,     sort_keys=__snake_case		,     ensure_ascii=__snake_case      ) + '\n'      )

      a		:   Dict	  =	0
      with open(__snake_case		,     'w'		,     encoding='utf-8'      ) as writer:
        writer.write('#version: 0.2\n'      )
        for bpe_tokens, token_index in sorted(self.bpe_ranks.items()		,     key=lambda __snake_case      : kv[1]      ):
          if index != token_index:
            logger.warning(
                F"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
                ' Please check that the tokenizer is not corrupted!'      )
            a		:   List[Any]	  =	token_index
          writer.write(' '.join(__snake_case      ) + '\n'      )
          index += 1

      return vocab_file, merge_file







    def      lowercase_			( self					:    Optional[int]		,     __snake_case					:    List[int]		,     __snake_case					:    Optional[List[int]] = None		,     __snake_case					:    bool = False      ):
      if already_has_special_tokens:
        return super().get_special_tokens_mask(
            token_ids_a=__snake_case		,     token_ids_a=__snake_case		,     already_has_special_tokens=__snake_case      )

      if token_ids_a is None:
        return [1] + ([0] * len(__snake_case      )) + [1]
      return [1] + ([0] * len(__snake_case      )) + [1, 1] + ([0] * len(__snake_case      )) + [1]







    def      lowercase_			( self					:    List[Any]		,     __snake_case					:    List[int]		,     __snake_case					:    Optional[List[int]] = None      ):
      a		:   Optional[Any]	  =	[self.sep_token_id]
      a		:   Dict	  =	[self.cls_token_id]

      if token_ids_a is None:
        return len(cls + token_ids_a + sep      ) * [0]
      return len(cls + token_ids_a + sep + sep + token_ids_a + sep      ) * [0]







    def      lowercase_			( self					:    int		,     __snake_case					:    str		,     __snake_case					:    Optional[Any]=False		,     **__snake_case					:    Union[str, Any]      ):
      a		:   str	  =	kwargs.pop('add_prefix_space'		,     self.add_prefix_space      )
      if (is_split_into_words or add_prefix_space) and (len(__snake_case      ) > 0 and not text[0].isspace()):
        a		:   Optional[Any]	  =	' ' + text
      return (text, kwargs)







    def      lowercase_			( self					:    Union[str, Any]		,     __snake_case					:    List[int]		,     __snake_case					:    Optional[List[int]] = None      ):
      return token_ids_a + [self.eos_token_id]







    def      lowercase_			( self					:    Optional[int]		,     __snake_case					:    "Conversation"      ):
      a		:   Dict	  =	[]
      for is_user, text in conversation.iter_texts():
        if is_user:
          # We need to space prefix as it's being done within blenderbot
          inputs.append(' ' + text      )
        else:
          # Generated responses should contain them already.
          inputs.append(__snake_case      )

      a		:   List[Any]	  =	'  '.join(__snake_case      )
      a		:   List[Any]	  =	self.encode(__snake_case      )
      if len(__snake_case      ) > self.model_max_length:
        a		:   int	  =	input_ids[-self.model_max_length :]
        logger.warning(F"""Trimmed input from conversation as it was longer than {self.model_max_length} tokens."""      )
      return input_ids




'''simple docstring'''






import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowerCAmelCase:   Tuple					=		logging.get_logger(__name__)

lowerCAmelCase:   Dict					=		'▁'

lowerCAmelCase:   Dict					=		{
    'vocab_file': 'vocab.json',
    'spm_file': 'sentencepiece.bpe.model',
}

lowerCAmelCase:   int					=		{
    'vocab_file': {
        'facebook/s2t-small-librispeech-asr': (
            'https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/vocab.json'
        ),
    },
    'spm_file': {
        'facebook/s2t-small-librispeech-asr': (
            'https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/sentencepiece.bpe.model'
        )
    },
}

lowerCAmelCase:   Any					=		{
    'facebook/s2t-small-librispeech-asr': 1_0_2_4,
}

lowerCAmelCase:   Optional[int]					=		['pt', 'fr', 'ru', 'nl', 'ro', 'it', 'es', 'de']

lowerCAmelCase:   List[Any]					=		{'mustc': MUSTC_LANGS}

class 				a__(   lowerCamelCase__      ):
    lowercase__					=       VOCAB_FILES_NAMES
    lowercase__					=       PRETRAINED_VOCAB_FILES_MAP
    lowercase__					=       MAX_MODEL_INPUT_SIZES
    lowercase__					=       ["""input_ids""", """attention_mask"""]

    lowercase__					=       []







    def __init__( self					:    int		,     __snake_case					:    int		,     __snake_case					:    Optional[Any]		,     __snake_case					:    Optional[Any]="<s>"		,     __snake_case					:    Optional[int]="</s>"		,     __snake_case					:    Union[str, Any]="<pad>"		,     __snake_case					:    str="<unk>"		,     __snake_case					:    Dict=False		,     __snake_case					:    int=False		,     __snake_case					:    str=None		,     __snake_case					:    Optional[int]=None		,     __snake_case					:    Optional[Dict[str, Any]] = None		,     **__snake_case					:    Union[str, Any]		,     ):
      a		:   Union[str, Any]	  =	{} if sp_model_kwargs is None else sp_model_kwargs

      super().__init__(
          bos_token=__snake_case		,     eos_token=__snake_case		,     unk_token=__snake_case		,     pad_token=__snake_case		,     do_upper_case=__snake_case		,     do_lower_case=__snake_case		,     tgt_lang=__snake_case		,     lang_codes=__snake_case		,     sp_model_kwargs=self.sp_model_kwargs		,     **__snake_case		,     )
      a		:   Tuple	  =	do_upper_case
      a		:   Optional[Any]	  =	do_lower_case

      a		:   List[str]	  =	load_json(__snake_case      )
      a		:   Dict	  =	{v: k for k, v in self.encoder.items()}
      a		:   int	  =	spm_file
      a		:   Tuple	  =	load_spm(__snake_case		,     self.sp_model_kwargs      )

      if lang_codes is not None:
        a		:   Any	  =	lang_codes
        a		:   str	  =	LANGUAGES[lang_codes]
        a		:   Tuple	  =	[F"""<lang:{lang}>""" for lang in self.langs]
        a		:   str	  =	{lang: self.sp_model.PieceToId(F"""<lang:{lang}>"""      ) for lang in self.langs}

        a		:   Optional[Any]	  =	self.lang_tokens
        a		:   Union[str, Any]	  =	tgt_lang if tgt_lang is not None else self.langs[0]

        self.set_tgt_lang_special_tokens(self._tgt_lang      )
      else:
        a		:   List[str]	  =	{}







    @property
    def      lowercase_			( self					:    Optional[Any]      ):
      return len(self.encoder      )







    @property
    def      lowercase_			( self					:    int      ):
      return self._tgt_lang







    @tgt_lang.setter
    def      lowercase_			( self					:    int		,     __snake_case					:    Optional[int]      ):
      a		:   Union[str, Any]	  =	new_tgt_lang
      self.set_tgt_lang_special_tokens(__snake_case      )







    def      lowercase_			( self					:    str		,     __snake_case					:    str      ):
      a		:   int	  =	self.lang_code_to_id[tgt_lang]
      a		:   int	  =	[lang_code_id]







    def      lowercase_			( self					:    Optional[int]		,     __snake_case					:    str      ):
      return self.sp_model.encode(__snake_case		,     out_type=__snake_case      )







    def      lowercase_			( self					:    List[str]		,     __snake_case					:    List[Any]      ):
      return self.encoder.get(__snake_case		,     self.encoder[self.unk_token]      )







    def      lowercase_			( self					:    List[Any]		,     __snake_case					:    int      ):
      return self.decoder.get(__snake_case		,     self.unk_token      )







    def      lowercase_			( self					:    Union[str, Any]		,     __snake_case					:    List[str]      ):
      a		:   List[Any]	  =	[]
      a		:   List[Any]	  =	''
      for token in tokens:
        # make sure that special tokens are not decoded using sentencepiece model
        if token in self.all_special_tokens:
          a		:   Union[str, Any]	  =	self.sp_model.decode(__snake_case      )
          out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
          a		:   Optional[int]	  =	[]
        else:
          current_sub_tokens.append(__snake_case      )
      a		:   Tuple	  =	self.sp_model.decode(__snake_case      )
      out_string += decoded.upper() if self.do_upper_case else decoded
      return out_string.strip()







    def      lowercase_			( self					:    int		,     __snake_case					:    List[Any]		,     __snake_case					:    List[str]=None      ):
      if token_ids_a is None:
        return self.prefix_tokens + token_ids_a + [self.eos_token_id]
      # We don't expect to process pairs, but leave the pair logic for API consistency
      return self.prefix_tokens + token_ids_a + token_ids_a + [self.eos_token_id]







    def      lowercase_			( self					:    Optional[int]		,     __snake_case					:    List[int]		,     __snake_case					:    Optional[List[int]] = None		,     __snake_case					:    bool = False      ):

      if already_has_special_tokens:
        return super().get_special_tokens_mask(
            token_ids_a=__snake_case		,     token_ids_a=__snake_case		,     already_has_special_tokens=__snake_case      )

      a		:   Optional[int]	  =	[1] * len(self.prefix_tokens      )
      a		:   Any	  =	[1]
      if token_ids_a is None:
        return prefix_ones + ([0] * len(__snake_case      )) + suffix_ones
      return prefix_ones + ([0] * len(__snake_case      )) + ([0] * len(__snake_case      )) + suffix_ones







    def      lowercase_			( self					:    Union[str, Any]      ):
      a		:   Union[str, Any]	  =	self.encoder.copy()
      vocab.update(self.added_tokens_encoder      )
      return vocab







    def __getstate__( self					:    Any      ):
      a		:   List[str]	  =	self.__dict__.copy()
      a		:   Union[str, Any]	  =	None
      return state







    def __setstate__( self					:    str		,     __snake_case					:    Dict      ):
      a		:   Dict	  =	d

      # for backward compatibility
      if not hasattr(self		,     'sp_model_kwargs'      ):
        a		:   int	  =	{}

      a		:   Any	  =	load_spm(self.spm_file		,     self.sp_model_kwargs      )







    def      lowercase_			( self					:    str		,     __snake_case					:    str		,     __snake_case					:    Optional[str] = None      ):
      a		:   Union[str, Any]	  =	Path(__snake_case      )
      assert save_dir.is_dir(), F"""{save_directory} should be a directory"""
      a		:   Any	  =	save_dir / (
          (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['vocab_file']
      )
      a		:   List[Any]	  =	save_dir / (
          (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['spm_file']
      )

      save_json(self.encoder		,     __snake_case      )

      if os.path.abspath(self.spm_file      ) != os.path.abspath(__snake_case      ) and os.path.isfile(self.spm_file      ):
        copyfile(self.spm_file		,     __snake_case      )
      elif not os.path.isfile(self.spm_file      ):
        with open(__snake_case		,     'wb'      ) as fi:
          a		:   Tuple	  =	self.sp_model.serialized_model_proto()
          fi.write(__snake_case      )

      return (str(__snake_case      ), str(__snake_case      ))
def  lowerCamelCase__			(		_A					,     _A							):
  a		:   List[Any]	  =	sentencepiece.SentencePieceProcessor(**_A							)
  spm.Load(str(_A							)							)
  return spm
def  lowerCamelCase__			(		_A							):
  with open(_A					,     'r'							) as f:
    return json.load(_A							)

def  lowerCamelCase__			(		_A					,     _A							):
  with open(_A					,     'w'							) as f:
    json.dump(_A					,     _A					,     indent=2							)